Using computational tools, researchers from the Johns Hopkins Kimmel Cancer Center and the Johns Hopkins University School of Medicine have developed a method to predict which patients with a primary liver cancer called hepatocellular carcinoma (HCC) would most benefit from combination treatment using immunotherapy and a targeted therapy that blocks the growth signals that the tumor depends on.
Ideally, modeling could get to the point where if multiple treatments were available for a particular cancer, researchers could help determine which of the treatments would be most effective, or which to avoid, Deshpande says.
Because such architectural features — both the fibroblast barrier the model flags and structural patterns the team measured in patient tumors — are visible before treatment begins, they could eventually help predict who will benefit, the researchers say.
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